A team of scientists at IBM Research in Zurich, have created an artificial version of neurons using phase-change materials to store and process data. These phase change based artificial neurons can be used to detect patterns and discover correlations in Big Data (real-time streams of event based data) and unsupervised machine learning at high speeds using very little energy. The results of the decade long research to use phase-change materials for memory applications, have recently been published in the journal Nature Nanotechnology. The research team is led by Evangelos Eleftheriou. The development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing is getting lot attention. This technology, foundation for event-based computations, could lead to the development of extremely dense neuromorphic computing systems (computers built to resemble brains) with…